compression

问题 I have a very weird problem.. I really do hope someone has an answer because I wouldn't know where else to ask. I am writing a cgi application in C++ which is executed by Apache and outputs HTML code. I am compressing the HTML output myself - from within my C++ application - since my web host doesn't support mod_deflate for some reason. I tested this with Firefox 2, Firefox 3, Opera 9, Opera 10, Google Chrome, Safari, IE6, IE7, IE8, even wget.. It works with ANYTHING except IE8. IE8 just says

问题 This is source PNG with transparency: http://i.imgur.com/7m0zIBp.png (13.3kB) optimized using compresspng.com: http://i.imgur.com/DHUiLuO.png (5.4kB) optimized using tinypng.com: http://i.imgur.com/rEE2hzg.png (5.6kB) optimized with gulp-imagemin+imagemin-pngquant: http://i.imgur.com/OTqI6lK.png (6.6kB) As you can see online tools are better than Gulp. Is there a way to improve PNG optimization with Gulp? Just in case, here's my gulp task: gulp.task('images', function() { return gulp.src(

问题 Is there a way to change the IIS compression module so that it does not put in Vary: Accept-Encoding in the Response Headers? I would rather it put in Vary: * or do nothing and let me put that value in myself... 回答1: Ok, apparently the IIS compression module forces the Vary header to be Accept-Encoding no matter what, so caching becomes tricky. For pages with authentication this is bad, because it will not detect that it's different based on the user cookie. I ended up rolling my own

问题 I'm writing a program for an assignment which has to implement LZW compression/decompression. I'm using the following algorithms for this: -compression w = NIL; while ( read a character k ) { if wk exists in the dictionary w = wk; else add wk to the dictionary; output the code for w; w = k; } -decompression read a character k; output k; w = k; while ( read a character k ) /* k could be a character or a code. */ { entry = dictionary entry for k; output entry; add w + entry[0] to dictionary; w

问题 How can I compress a video file in Android before uploading to a remote server? I'm not looking to zip up the file, because I don't think that will help much. I want to compress the video and re-encode it with a lower bit-rate or resolution. The idea is to get a standard 360х480, 30 FPS video file from every device. This way I can avoid users with better cameras being forced to upload huge video files. I know iOS makes it fairly simple to force video file resolutions. 10 second video recorded

问题 I have zip file with following internal structure: file1.txt directoryABC fileA.txt fileB.txt fileC.txt What would be the best way to extract files from "directoryABC" folder to a target location on hard drive? For example if target location is "C:\temp" then its content should be: temp directoryABC fileA.txt fileB.txt fileC.txt Also in certain situations I'd want to extract only content of the "directoryABC" so the result would be: temp fileA.txt fileB.txt fileC.txt How can I accomplish this

问题 I recently asked a question regarding how to save large python objects to file. I had previously run into problems converting massive Python dictionaries into string and writing them to file via write() . Now I am using pickle. Although it works, the files are incredibly large (> 5 GB). I have little experience in the field of such large files. I wanted to know if it would be faster, or even possible, to zip this pickle file prior to storing it to memory. 回答1: Python code would be extremely

问题 After reading about how gzip compression works it got me thinking. If the Origin and Proxy server (CDN) both support gzip is adding a Vary: Accept-Encoding header necessary? 回答1: The Vary: Accept-Encoding header has more to do with caching than compression. When the Vary: Accept-Encoding header is present, it tells the client that the file can be cached/is the same whether or not the client requests compression. If for some reason the client has an uncompressed version of the file in its

问题 I have read several times that turning on compression in HDF5 can lead to better read/write performance. I wonder what ideal settings can be to achieve good read/write performance at: data_df.to_hdf(..., format='fixed', complib=..., complevel=..., chunksize=...) I'm already using fixed format (i.e. h5py ) as it's faster than table . I have strong processors and do not care much about disk space. I often store DataFrame s of float64 and str types in files of approx. 2500 rows x 9000 columns.

问题 I have started to look into Hadoop. If my understanding is right i could process a very big file and it would get split over different nodes, however if the file is compressed then the file could not be split and wold need to be processed by a single node (effectively destroying the advantage of running a mapreduce ver a cluster of parallel machines). My question is, assuming the above is correct, is it possible to split a large file manually in fixed-size chunks, or daily chunks, compress